contour¶

This section provides examples of how to use the contour function. At a minimum, the plot function requires the following keywords:

df: a pandas DataFrame
x: the name of the DataFrame column containing the x-axis data
y: the name of the DataFrame column containing the y-axis data
z: the name of the DataFrame column containing the z-axis data

Setup¶

Imports¶

In [1]:

%load_ext autoreload
%autoreload 2
%matplotlib inline
import fivecentplots as fcp
import pandas as pd
import numpy as np
import os, sys, pdb
osjoin = os.path.join
db = pdb.set_trace

Sample data¶

In [2]:

df = pd.read_csv(osjoin(os.path.dirname(fcp.__file__), 'tests', 'fake_data_contour.csv'))
df.head()

Out[2]:

	Experiment	Batch	X	Y	Value
0	Control	101	1	-4	3.5
1	Control	101	1	-2	2.1
2	Control	101	1	0	3.3
3	Control	101	1	2	3.2
4	Control	101	1	4	4.0

Set theme¶

In [3]:

#fcp.set_theme('gray')
#fcp.set_theme('white')

Other¶

In [4]:

SHOW = False

Basic contour¶

In [5]:

fcp.contour(df=df, x='X', y='Y', z='Value', row='Batch', col='Experiment', filled=False,
            cbar=False, xmin=-3, xmax=3, ymin=-3, ymax=3, ax_size=[250,250], show=SHOW, contour_width=2,
            label_rc_font_size=12)

Filled contour¶

Next we can fill the contours using the keyword filled or contour_filled and increase the number of contour lines from the default of 20 to a custom value using the keyword levels or contour_levels:

In [6]:

fcp.contour(df=df, x='X', y='Y', z='Value', row='Batch', col='Experiment', filled=True,
            cbar=True, xmin=-3, xmax=3, ymin=-3, ymax=3, ax_size=[250,250], show=SHOW,
            label_rc_font_size=12, levels=40)

And with a fixed z-range:

In [7]:

fcp.contour(df=df, x='X', y='Y', z='Value', row='Batch', col='Experiment', filled=True,
            cbar=True, xmin=-3, xmax=3, ymin=-3, ymax=3, ax_size=[250,250], show=SHOW,
            label_rc_font_size=12, zmin=1, zmax=3, levels=40)